Songshan Yang

Songshan Yang

Education

Academic Work Experience

Featured Publications

( # : Corresponding author, * : Supervised student)

Yilin Zhang*, Songshan Yang #, Yunan Wu, Lan Wang (2026+). Partial Gini Covariance-based Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors. Journal of the American Statistical Association.

Yifan Gu *, Hanfang Yang, Songshan Yang #, Hui Zou # (2026+). Collaborative Inference for Sparse High-Dimensional Models with Non-Shared Data. Journal of the American Statistical Association. (Alphabetical order)

Songshan Yang, Delin Zhao, Runze Li (2026+). Statistical Inference for High-dimensional Partially Linear Models via Debiased Rank Lasso. Journal of Machine Learning Research.

Songshan Yang, Yifan Gu *, Hanfang Yang, Xuming He (2026). Communication-Efficient and Distributed-Oracle Estimation for High-Dimensional Quantile Regression. The Annals of Statistics, 54(1),442-465.

Jiawei Wen, Songshan Yang #, Christina Dan Wang, Yifan Jiang, Runze Li (2025). Feature-splitting Algorithms for Ultrahigh Dimensional Quantile Regression. Journal of Econometrics, 249(a), 105426.

Songshan Yang, Shurong Zheng, Runze Li (2024). A New Test for High Dimensional Two-Sample Mean Problems with Consideration of Correlation Structure. The Annals of Statistics, 52(5), 2217-2240.

Zhanrui Cai, Changcheng Li, Jiawei Wen, Songshan Yang # (2024). Asset Splitting Algorithm for Ultrahigh Dimensional Portfolio Selection and Its Theoretical Property. Journal of Econometrics, 239(2), 10529. (Alphabetical order)

Zhaoxue Tong, Zhanrui Cai #, Songshan Yang #, Runze Li (2023). Model-free Conditional Feature Screening with FDR Control. Journal of the American Statistical Association, 118, (544), 2575-2587.

Le Bao, Changcheng Li #, Runze Li, Songshan Yang # (2022). Causal Structural Learning on MPHIA Individual Dataset. Journal of the American Statistical Association, 117(540), 1642-1655. (Alphabetical order)

Songshan Yang #, Jiawei Wen, Xiang Zhan, Daniel Kifer (2019). ET-lasso: A New Efficient Tuning of Lasso-type Regularization for High-dimensional Data. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Oral), 607-616.

Editorial Service